Give the agent read-only credentials. Credentials are encrypted at rest, and connections are encrypted in transit. See our Security page for details.

Can it handle large datasets?

Yes. The agent queries your database where it lives and brings back aggregates or samples.

Data Analysis & Reporting

Use Internal agents with sandbox and integrations to query data, summarize trends, and deliver reports on a schedule or on demand.

Typical use: A scheduled Loop runs every Monday: the agent queries a database or sheet and posts a summary to Slack.

The Challenge

Data teams struggle with repetitive analysis work:

Manual report generation - Hours spent copying data into spreadsheets
Delayed insights - By the time reports are ready, data is outdated
Limited bandwidth - Analysts spend their time on routine reports
Inconsistent analysis - Different people analyze data differently
Scaling bottleneck - Can’t keep up with growing data needs

The cost of slow analysis:

Missed opportunities from delayed insights
Poor decisions based on outdated data
Analyst burnout from repetitive work
Inability to scale data-driven culture

The Solution

Auteryn data agents connect to your databases, APIs, and files to automatically analyze data, generate insights, and create beautiful reports on demand or on schedule.

Key Capabilities

Multi-Source Analysis

Connect to SQL databases, APIs, CSV files, Google Sheets, and more. Combine data from multiple sources.

Automated Reports

Generate PDF, Excel, or HTML reports automatically. Schedule daily, weekly, or monthly.

Smart Insights

AI identifies trends, anomalies, and patterns you might miss. Highlights what matters.

Custom Visualizations

Create charts, graphs, and diagrams automatically. Export as images, HTML, or presentation slides.

Natural Language Queries

Ask questions in plain English: “Show me top customers by revenue this quarter.”

Scheduled Delivery

Automatically send reports to stakeholders via email, Slack, or dashboard.

How It Works

Connect Your Data Sources

Use read-only credentials. Postgres, Snowflake and BigQuery each have a Featured MCP Integration. For other databases the agent runs a client in the sandbox with credentials you supply, and Google Sheets works through Google Workspace.
Define Analysis Templates

Create reusable analysis workflows: metrics to track, visualizations to generate, insights to highlight.
Schedule or Trigger

Run reports on a schedule (daily, weekly or monthly), or start one from a Slack message or the REST API.
Deliver Insights

Reports automatically sent to email, Slack, dashboard, or stored in cloud storage.

Example workflow

Scheduled Loop every weekday at 09:00 UTC: the agent runs SQL in the sandbox (or calls an integration) and posts a KPI summary to #analytics on Slack.

Features in Detail

Intelligent Data Processing

The agent automatically:

Cleans data - Handles missing values, duplicates, and formatting issues
Joins sources - Combines data from multiple databases or APIs
Calculates metrics - Revenue, growth rates, conversion funnels, cohorts
Detects anomalies - Flags unusual patterns or outliers
Generates summaries - Key takeaways and recommendations

Deep Analytics

Beyond basic reporting:

Trend analysis - Identify patterns over time
Cohort analysis - Track user behavior by segment
Funnel analysis - Conversion optimization insights
Predictive modeling - Forecast future trends
A/B test analysis - Statistical significance testing
Customer segmentation - RFM analysis, clustering

Flexible Output Formats

Generate reports in any format:

PDF reports - Professional, branded documents
Excel workbooks - Interactive spreadsheets with charts
HTML dashboards - Web-based, shareable dashboards
PowerPoint slides - Ready for presentations
Slack messages - Quick updates with key metrics
Email summaries - Automated digest emails

Integration Options

SQL databases (via sandbox)

Connect to PostgreSQL, MySQL, and others by running the client in the sandbox with credentials you supply. Use read-only accounts for safety.

Data warehouses (via MCP / sandbox)

Query Snowflake or BigQuery through their Featured MCP Integrations (read-only), and other warehouses with their CLI or SDK in the sandbox.

APIs

REST APIs via Custom MCP or connected integrations when configured.

Spreadsheets

Read and write CSV/Excel files in the sandbox; use Google Sheets when Google Workspace is connected.

BI tools (export)

Produce CSV/JSON/HTML outputs you can import into your existing dashboards. No native Tableau/Power BI connector.

Cloud storage

Store reports in the sandbox or Google Drive (when connected); other object stores via Custom MCP or their CLI.

Use Cases

Executive Dashboards

Automated daily/weekly executive summaries:

Revenue and growth metrics
Customer acquisition and churn
Product usage statistics
Key performance indicators

Marketing Analytics

Campaign performance and attribution:

Channel ROI analysis
Conversion funnel tracking
Customer lifetime value
A/B test results

Sales Reporting

Pipeline and performance tracking:

Sales forecasting
Win/loss analysis
Rep performance metrics
Deal velocity tracking

Product Analytics

User behavior and engagement:

Feature adoption rates
User retention cohorts
Engagement metrics
Churn prediction

Pricing

Data analysis automation scales with your needs:

Free: $0/month — 1,000 credits
Pro: $29/month — 15,000 credits ($24/mo billed annually)
Business: $99/month — 60,000 pooled credits ($83/mo billed annually)
Enterprise: Custom pricing for high-volume analytics

Actual report throughput depends on data size and task complexity. See Pricing for full plan limits and credit rates.

Get Started

Sign up free - No credit card required
Follow the quickstart - Create your first agent in 10 minutes
Use the data-analysis Skill - attach it to your Agent in the Console
Connect your data - through a Featured MCP or Custom MCP Integration, or with credentials the agent uses in its sandbox

Questions?

Is my data secure? Give the agent read-only credentials. Credentials are encrypted at rest, and connections are encrypted in transit. See Security for details.
What data sources are supported? SQL databases, data warehouses, REST APIs, GraphQL, spreadsheets, and cloud storage.
Can it handle large datasets? Yes. The agent queries your database where it lives and brings back aggregates or samples.
How do I customize reports? Describe the report in the agent’s instructions or in a Skill, or have it run your own Python or SQL scripts.
Can it send alerts? Yes. A scheduled Loop can check a metric against a threshold you set and post to Slack or send an email when it crosses.

View all FAQs →